Collects software dedicated to predicting specific properties of peptides

Implements the blood brain barrier score described in: J. Med. Chem. 2019, 62, 21, 9824-9836 (https://doi.org/10.1021/acs.jmedchem.9b01220)

Predictors for Blood-Brain Barrier Permeability with resampling strategies based on B3DB database.

Multi-objective generative AI for designing novel brain-targeting small molecules.

Virtual laboratory for rational drug design and discovery at the blood-brain barrier supervised by Prof. Dr. Sergey Shityakov, MD, PhD.

BBBP Explainer is a code to generate structural alerts of blood-brain barrier penetrating and non-penetrating drugs using Local Interpretable Model-Agnostic Explanations (LIME) of machine learning models from BBBP dataset.

Antipsychotic drugs or neuroleptics are widely used in the treatment of psychosis as a manifestation of schizophrenia and bipolar disorder. However, their effectiveness largely depends on the blood-brain barrier (BBB) permeation (pharmacokinetics, PK) and drug-receptor pharmacodynamics (PD). Therefore, in this study, we developed and implemented…

With a focus on BBB modulation, safety, and translational relevance, this academic research project investigates targeted ultrasound and microbubble-mediated approaches for improved CNS and brain tumor drug delivery.

Individual project for 4th year where models were trained to predict whether a drug can pass through the Blood-Brain Barrier using its chemical properties but also its side effects and indications. Notebooks & Streamlit App Available

A modelisation of Blood Brain Barrier permeability through active transporters

An analysis toolkit for the estimation of neuroimaging observables

GSEA-based transcriptomic analysis of COVID-19 impact on blood-brain barrier gene expression using GEO datasets (GSE167000, GSE179923)

Graph molecular learning to predict blood-brain-barrier penetration and CNS drug delivery.

A graph neural network to predict blood brain barrier permeability of a drug

Interpretable GNN for Blood-Brain Barrier prediction with molecular generation and structure-activity analysis.

🧠 ML pipeline predicting CNS Blood-Brain Barrier permeability — 60+ RDKit descriptors, 6 classifiers (AUC ~0.93), SHAP explainability, mechanistic Kp,uu,brain framework & PBPK ODE simulation. Trained on B3DB and BBBP benchmark.

Blood-Brain Barrier permeability predictor using hybrid GAT-GCN-GraphSAGE architecture. 0.9612 AUC on 7,807-compound external validation.

In Silico Evaluation of Haloalkylated Human 18kDa Translocator Protein PET Tracer Candidates for Traumatic Brain Injury Neuroinflammation